{"id":"W2143093088","doi":"10.1093/bioinformatics/btp378","title":"ISOLATE: a computational strategy for identifying the primary origin of cancers using high-throughput sequencing","year":2009,"lang":"en","type":"article","venue":"Bioinformatics","topic":"Cancer Diagnosis and Treatment","field":"Medicine","cited_by":40,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Toronto","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Computational biology; Biology; Profiling (computer programming); Sample size determination; Gene expression profiling; Computer science; Gene; Machine learning; Artificial intelligence; Gene expression; Genetics; Statistics; Mathematics","routes":{"ca_aff":true,"ca_fund":true,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001929063,0.001116254,0.001233694,0.001618092,0.000687897,0.001163974,0.002127918,0.001291302,0.003768636],"category_scores_gemma":[0.007000012,0.0007129429,0.001599595,0.0009910252,0.0006455717,0.0009178022,0.001240467,0.001307443,0.001037935],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00066371,"about_ca_system_score_gemma":0.002110593,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.004867741,"about_ca_topic_score_gemma":0.009519019,"domain_scores_codex":[0.9995276,0.0001786126,0.0000234635,0.0001173662,0.0001125386,0.00004054873],"domain_scores_gemma":[0.9970824,0.002217209,0.0001350847,0.000216027,0.0002246936,0.0001246614],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0007805157,0.0002761877,0.009493216,0.0003088838,0.0004439755,0.0004008649,0.0001417158,0.7917385,0.005177949,0.008105471,0.01416822,0.1689646],"study_design_scores_gemma":[0.00002870922,0.00002367523,0.0002763685,0.000004136899,0.00001796884,0.00002811268,0.000008536099,0.9951168,0.0005683701,0.003401611,0.0005194199,0.000006272618],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.03097482,0.0001357082,0.9605396,0.0004618669,0.00005012951,0.000174939,0.001146412,0.005522467,0.0009939934],"genre_scores_gemma":[0.269435,0.0001887128,0.7202638,0.0005911005,0.000169731,0.0009365479,0.005131607,0.00091406,0.002369467],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.004867741,"threshold_uncertainty_score":0.01260728,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.09569313300894752,"score_gpt":0.3525244095334745,"score_spread":0.256831276524527,"validation_status":"score_only:v0-immature-baseline","note":"Baseline scores from an immature model (maturity gate not passed). Scores rank; they never assert a category."}}